Programming by Demonstration Using Version Space Algebra

By Tessa A. Lau, Steven A. Wolfman, Pedro M. Domingos, Daniel S. Weld. 2003

225 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Code Generation & Program Synthesis, Human-Computer Interaction

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Citations in the corpus

Learning with Latent Language (2017, neutral): “Domain-speciﬁc structure like version space algebras (Lau et al., 2003) or type systems (Kitzelmann and Schmid, 2006) can be brought to bear on the search problem, and the bias inherent in the syntax of the formal language provides a strong prior.”
Errudite: Scalable, Reproducible, and Testable Error Analysis (2019, methodology): “It has been widely applied to tasks like data wrangling (Kandel et al., 2011) and text editing (Lau et al., 2003).”
Automating string processing in spreadsheets using input-output examples (2011, unknown): “Text-editing using Demonstrations SMARTedit [11] is a Programming by Demonstration (PBD) system for learning textediting commands, where the primitive program statements include moving the cursor to a new position and inserting/deleting text.”
A Machine Learning Framework for Programming by Example (2013, methodology): “using a version space (Lau et al., 2003), thus sidestepping the issue of searching for programs using general classes of functions.”
Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models (2022, background): “These techniques work on a subset of the language components relevant to the domain known as Domain-Specific Languages (DSLs).”
Learning Semantic String Transformations from Examples (2012, background): “Programming-by-demonstration systems for text-editing like SMARTedit [14] or simultaneous editing [15] require the user to provide a complete demonstration or trace, where the demonstration consists of a sequence of the editor state after each primitive action, really spelling out how to do the tran”
NLyze: interactive programming by natural language for spreadsheet data analysis and manipulation (2014, unknown): “For PBD these domains include text manipulation [19] and table transformations [13].”
On the difficulty of benchmarking inductive program synthesis methods (2017, methodology): “Building on the use of version-space algebras for programming by demonstration [18], Flash Fill assumes few example inputs and must make simplifying assumptions about the problem space.”
Spreadsheet table transformations from examples (2011, background): “To find an associative program that is consistent for all examples, the check at line [14] is extended to determine if the associative program AssocProg is consistent with each example.”
Predicting a Correct Program in Programming by Example (2015, methodology): “These techniques have been developed for a wide variety of domains including repetitive text-editing [15], syntactic string transformations [8], semantic string transformations [25], table transformations [12], and number transformations [26].”
Program Synthesis Using Natural Language (2015, background): “For PBD these domains include text manipulation [28] and table transformations [23] among others [7].”
Learning Programs: A Hierarchical Bayesian Approach (2010, methodology): “An example we consider in this paper is text editing (Lau et al., 2003).”
A Decision-Theoretic Model of Assistance (2007, background): “This work is also closely related to learning from demonstration or programming by demonstration (Atkeson & Schaal, 1997; Cypher, 1993; Lau, Wolfman, Domingos, & Weld, 2003 ).”
A new representation and associated algorithms for generalized planning (2011, background): “Approaches like [20] address the significantly different problem of using a given segment of a user’s actions (e.”